A model for on-line selection of roughing parameters of the EDM process

Code

L2-6193 (C) - included in ARIS records

Head

PhD Mihael Junkar

Period

7/1/2004 - 6/30/2006

Range in 2006

0.12 FTE and 133 unpaid hours

Science

Engineering sciences and technologies (6)
Other (1)

Reseacher status

Researcher (7)
Junior expert or technical associate (0)

Education

Doctor's degree (5)
Other (2)

Sex

Man (7)

Status

Employed at RO and RRD (4)
No data on employment in RO (1)
Retired (1)
Deceased (1)

No. of publications

1–9 (1)
10–99 (1)
100–999 (5)

Projects / Programmes source: ARIS

source: ARIS

A model for on-line selection of roughing parameters of the EDM process

Research activity

Code	Science	Field	Subfield
2.10.00	Engineering sciences and technologies	Manufacturing technologies and systems

Code	Science	Field
T130	Technological sciences	Production technology

Keywords

EDM, electrical discharge machining, inductive machine learning, non-parametric modelling, rough machining, process monitoring

Evaluation (rules)

source: COBISS

Evaluation of bibliographic research performance indicators according to ARIS methodology

Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases

source: WoS

source: Scopus

source: COBISS

Researchers (7)

no.	Code	Name and surname	Research area	Role	Period	No. of publicationsNo. of publications
1.	09006	PhD Mihael Junkar	Manufacturing technologies and systems	Head	2004 - 2006	552
2.	24419	Boštjan Juriševič	Manufacturing technologies and systems	Researcher	2004 - 2006	62
3.	17076	PhD Davorin Kramar	Manufacturing technologies and systems	Researcher	2004 - 2006	447
4.	12260	PhD Andrej Lebar	Manufacturing technologies and systems	Researcher	2004 - 2006	309
5.	23469	PhD Henri Orbanić	Manufacturing technologies and systems	Junior researcher	2004 - 2006	166
6.	18000	Bruno Stropnik		Technical associate	2004 - 2005	1
7.	18553	PhD Joško Valentinčič	Manufacturing technologies and systems	Researcher	2004 - 2006	444

Organisations (1)

no.	Code	Research organisation	City	Registration number	No. of publicationsNo. of publications
1.	0782	University of Ljubljana, Faculty of Mechanical Engineering	Ljubljana	1627031	29,201

Abstract

The sinking electrical discharge machining process (EDM) is performed in the gap between the electrode and the workpiece. The gap is filled with dielectric and the size of the gap is controlled by the servo system of the EDM machine. Electric pulses produced by electric generator cause a breakdown of the dielecric in the gap. After the breakdown, the discharge occurs, which causes a material removal in the place where it occurs. The material removal rate depends on the machining parameters (discharge current, discharge duration etc.), which are grouped into machining regimes. To achieve the highest material removal rate on the given machining surface, the roughing regime has to be selected according to the eroding surface size, which is defined as the projection of the machining surface to the plane perpendicular to the direction of the electrode movement. Most often, the eroding surface size varies during the machining. Thus, the roughing regime has to be selected on-line. Since the material removal rate of the EDM process is relatively small, the on-line selection of the roughing regime is essential for fast and cheap production. The system for on-line selection of the roughing regime will be based on the acquisition of the voltage signal in the gap. The attributes on the voltage signal will be attained by inductive machine learning methods and their values will be calculated on-line by the analysator. Non-parametric model, which will on-line select the appropriate roughing regime, will be build by the conditional average estimator method. The model will perform the on-line selection of the roughing regime and thus the highest material removal rate on the given machining surface will be obtained.